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<h1><a href="aiplatform_v1beta1.html">Vertex AI API</a> . <a href="aiplatform_v1beta1.projects.html">projects</a> . <a href="aiplatform_v1beta1.projects.locations.html">locations</a> . <a href="aiplatform_v1beta1.projects.locations.featureGroups.html">featureGroups</a> . <a href="aiplatform_v1beta1.projects.locations.featureGroups.featureMonitors.html">featureMonitors</a> . <a href="aiplatform_v1beta1.projects.locations.featureGroups.featureMonitors.featureMonitorJobs.html">featureMonitorJobs</a></h1>
<h2>Instance Methods</h2>
<p class="toc_element">
  <code><a href="#close">close()</a></code></p>
<p class="firstline">Close httplib2 connections.</p>
<p class="toc_element">
  <code><a href="#create">create(parent, body=None, featureMonitorJobId=None, x__xgafv=None)</a></code></p>
<p class="firstline">Creates a new feature monitor job.</p>
<p class="toc_element">
  <code><a href="#get">get(name, x__xgafv=None)</a></code></p>
<p class="firstline">Get a feature monitor job.</p>
<p class="toc_element">
  <code><a href="#list">list(parent, filter=None, orderBy=None, pageSize=None, pageToken=None, x__xgafv=None)</a></code></p>
<p class="firstline">List feature monitor jobs.</p>
<p class="toc_element">
  <code><a href="#list_next">list_next()</a></code></p>
<p class="firstline">Retrieves the next page of results.</p>
<h3>Method Details</h3>
<div class="method">
    <code class="details" id="close">close()</code>
  <pre>Close httplib2 connections.</pre>
</div>

<div class="method">
    <code class="details" id="create">create(parent, body=None, featureMonitorJobId=None, x__xgafv=None)</code>
  <pre>Creates a new feature monitor job.

Args:
  parent: string, Required. The resource name of FeatureMonitor to create FeatureMonitorJob. Format: `projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_monitor}` (required)
  body: object, The request body.
    The object takes the form of:

{ # Vertex AI Feature Monitor Job.
  &quot;createTime&quot;: &quot;A String&quot;, # Output only. Timestamp when this FeatureMonitorJob was created. Creation of a FeatureMonitorJob means that the job is pending / waiting for sufficient resources but may not have started running yet.
  &quot;description&quot;: &quot;A String&quot;, # Optional. Description of the FeatureMonitor.
  &quot;driftBaseFeatureMonitorJobId&quot;: &quot;A String&quot;, # Output only. FeatureMonitorJob ID comparing to which the drift is calculated.
  &quot;driftBaseSnapshotTime&quot;: &quot;A String&quot;, # Output only. Data snapshot time comparing to which the drift is calculated.
  &quot;featureSelectionConfig&quot;: { # Feature selection configuration for the FeatureMonitor. # Output only. Feature selection config used when creating FeatureMonitorJob.
    &quot;featureConfigs&quot;: [ # Optional. A list of features to be monitored and each feature&#x27;s drift threshold.
      { # Feature configuration.
        &quot;driftThreshold&quot;: 3.14, # Optional. Drift threshold. If calculated difference with baseline data larger than threshold, it will be considered as the feature has drift. If not present, the threshold will be default to 0.3. Must be in range [0, 1).
        &quot;featureId&quot;: &quot;A String&quot;, # Required. The ID of the feature resource. Final component of the Feature&#x27;s resource name.
      },
    ],
  },
  &quot;finalStatus&quot;: { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Final status of the FeatureMonitorJob.
    &quot;code&quot;: 42, # The status code, which should be an enum value of google.rpc.Code.
    &quot;details&quot;: [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
      {
        &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
      },
    ],
    &quot;message&quot;: &quot;A String&quot;, # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
  },
  &quot;jobSummary&quot;: { # Summary from the FeatureMonitorJob. # Output only. Summary from the FeatureMonitorJob.
    &quot;featureStatsAndAnomalies&quot;: [ # Output only. Features and their stats and anomalies
      { # Stats and Anomaly generated by FeatureMonitorJobs. Anomaly only includes Drift.
        &quot;distributionDeviation&quot;: 3.14, # Deviation from the current stats to baseline stats. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.
        &quot;driftDetected&quot;: True or False, # If set to true, indicates current stats is detected as and comparing with baseline stats.
        &quot;driftDetectionThreshold&quot;: 3.14, # This is the threshold used when detecting drifts, which is set in FeatureMonitor.FeatureSelectionConfig.FeatureConfig.drift_threshold
        &quot;featureId&quot;: &quot;A String&quot;, # Feature Id.
        &quot;featureMonitorId&quot;: &quot;A String&quot;, # The ID of the FeatureMonitor that this FeatureStatsAndAnomaly generated according to.
        &quot;featureMonitorJobId&quot;: &quot;A String&quot;, # The ID of the FeatureMonitorJob that generated this FeatureStatsAndAnomaly.
        &quot;featureStats&quot;: &quot;&quot;, # Feature stats. e.g. histogram buckets. In the format of tensorflow.metadata.v0.DatasetFeatureStatistics.
        &quot;statsTime&quot;: &quot;A String&quot;, # The timestamp we take snapshot for feature values to generate stats.
      },
    ],
    &quot;totalSlotMs&quot;: &quot;A String&quot;, # Output only. BigQuery slot milliseconds consumed.
  },
  &quot;labels&quot;: { # Optional. The labels with user-defined metadata to organize your FeatureMonitorJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureMonitor(System labels are excluded).&quot; System reserved label keys are prefixed with &quot;aiplatform.googleapis.com/&quot; and are immutable.
    &quot;a_key&quot;: &quot;A String&quot;,
  },
  &quot;name&quot;: &quot;A String&quot;, # Identifier. Name of the FeatureMonitorJob. Format: `projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_monitor}/featureMonitorJobs/{feature_monitor_job}`.
  &quot;triggerType&quot;: &quot;A String&quot;, # Output only. Trigger type of the Feature Monitor Job.
}

  featureMonitorJobId: string, Optional. Output only. System-generated ID for feature monitor job.
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # Vertex AI Feature Monitor Job.
  &quot;createTime&quot;: &quot;A String&quot;, # Output only. Timestamp when this FeatureMonitorJob was created. Creation of a FeatureMonitorJob means that the job is pending / waiting for sufficient resources but may not have started running yet.
  &quot;description&quot;: &quot;A String&quot;, # Optional. Description of the FeatureMonitor.
  &quot;driftBaseFeatureMonitorJobId&quot;: &quot;A String&quot;, # Output only. FeatureMonitorJob ID comparing to which the drift is calculated.
  &quot;driftBaseSnapshotTime&quot;: &quot;A String&quot;, # Output only. Data snapshot time comparing to which the drift is calculated.
  &quot;featureSelectionConfig&quot;: { # Feature selection configuration for the FeatureMonitor. # Output only. Feature selection config used when creating FeatureMonitorJob.
    &quot;featureConfigs&quot;: [ # Optional. A list of features to be monitored and each feature&#x27;s drift threshold.
      { # Feature configuration.
        &quot;driftThreshold&quot;: 3.14, # Optional. Drift threshold. If calculated difference with baseline data larger than threshold, it will be considered as the feature has drift. If not present, the threshold will be default to 0.3. Must be in range [0, 1).
        &quot;featureId&quot;: &quot;A String&quot;, # Required. The ID of the feature resource. Final component of the Feature&#x27;s resource name.
      },
    ],
  },
  &quot;finalStatus&quot;: { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Final status of the FeatureMonitorJob.
    &quot;code&quot;: 42, # The status code, which should be an enum value of google.rpc.Code.
    &quot;details&quot;: [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
      {
        &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
      },
    ],
    &quot;message&quot;: &quot;A String&quot;, # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
  },
  &quot;jobSummary&quot;: { # Summary from the FeatureMonitorJob. # Output only. Summary from the FeatureMonitorJob.
    &quot;featureStatsAndAnomalies&quot;: [ # Output only. Features and their stats and anomalies
      { # Stats and Anomaly generated by FeatureMonitorJobs. Anomaly only includes Drift.
        &quot;distributionDeviation&quot;: 3.14, # Deviation from the current stats to baseline stats. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.
        &quot;driftDetected&quot;: True or False, # If set to true, indicates current stats is detected as and comparing with baseline stats.
        &quot;driftDetectionThreshold&quot;: 3.14, # This is the threshold used when detecting drifts, which is set in FeatureMonitor.FeatureSelectionConfig.FeatureConfig.drift_threshold
        &quot;featureId&quot;: &quot;A String&quot;, # Feature Id.
        &quot;featureMonitorId&quot;: &quot;A String&quot;, # The ID of the FeatureMonitor that this FeatureStatsAndAnomaly generated according to.
        &quot;featureMonitorJobId&quot;: &quot;A String&quot;, # The ID of the FeatureMonitorJob that generated this FeatureStatsAndAnomaly.
        &quot;featureStats&quot;: &quot;&quot;, # Feature stats. e.g. histogram buckets. In the format of tensorflow.metadata.v0.DatasetFeatureStatistics.
        &quot;statsTime&quot;: &quot;A String&quot;, # The timestamp we take snapshot for feature values to generate stats.
      },
    ],
    &quot;totalSlotMs&quot;: &quot;A String&quot;, # Output only. BigQuery slot milliseconds consumed.
  },
  &quot;labels&quot;: { # Optional. The labels with user-defined metadata to organize your FeatureMonitorJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureMonitor(System labels are excluded).&quot; System reserved label keys are prefixed with &quot;aiplatform.googleapis.com/&quot; and are immutable.
    &quot;a_key&quot;: &quot;A String&quot;,
  },
  &quot;name&quot;: &quot;A String&quot;, # Identifier. Name of the FeatureMonitorJob. Format: `projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_monitor}/featureMonitorJobs/{feature_monitor_job}`.
  &quot;triggerType&quot;: &quot;A String&quot;, # Output only. Trigger type of the Feature Monitor Job.
}</pre>
</div>

<div class="method">
    <code class="details" id="get">get(name, x__xgafv=None)</code>
  <pre>Get a feature monitor job.

Args:
  name: string, Required. The name of the FeatureMonitorJob resource. Format: `projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_monitor}/featureMonitorJobs/{feature_monitor_job}` (required)
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # Vertex AI Feature Monitor Job.
  &quot;createTime&quot;: &quot;A String&quot;, # Output only. Timestamp when this FeatureMonitorJob was created. Creation of a FeatureMonitorJob means that the job is pending / waiting for sufficient resources but may not have started running yet.
  &quot;description&quot;: &quot;A String&quot;, # Optional. Description of the FeatureMonitor.
  &quot;driftBaseFeatureMonitorJobId&quot;: &quot;A String&quot;, # Output only. FeatureMonitorJob ID comparing to which the drift is calculated.
  &quot;driftBaseSnapshotTime&quot;: &quot;A String&quot;, # Output only. Data snapshot time comparing to which the drift is calculated.
  &quot;featureSelectionConfig&quot;: { # Feature selection configuration for the FeatureMonitor. # Output only. Feature selection config used when creating FeatureMonitorJob.
    &quot;featureConfigs&quot;: [ # Optional. A list of features to be monitored and each feature&#x27;s drift threshold.
      { # Feature configuration.
        &quot;driftThreshold&quot;: 3.14, # Optional. Drift threshold. If calculated difference with baseline data larger than threshold, it will be considered as the feature has drift. If not present, the threshold will be default to 0.3. Must be in range [0, 1).
        &quot;featureId&quot;: &quot;A String&quot;, # Required. The ID of the feature resource. Final component of the Feature&#x27;s resource name.
      },
    ],
  },
  &quot;finalStatus&quot;: { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Final status of the FeatureMonitorJob.
    &quot;code&quot;: 42, # The status code, which should be an enum value of google.rpc.Code.
    &quot;details&quot;: [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
      {
        &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
      },
    ],
    &quot;message&quot;: &quot;A String&quot;, # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
  },
  &quot;jobSummary&quot;: { # Summary from the FeatureMonitorJob. # Output only. Summary from the FeatureMonitorJob.
    &quot;featureStatsAndAnomalies&quot;: [ # Output only. Features and their stats and anomalies
      { # Stats and Anomaly generated by FeatureMonitorJobs. Anomaly only includes Drift.
        &quot;distributionDeviation&quot;: 3.14, # Deviation from the current stats to baseline stats. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.
        &quot;driftDetected&quot;: True or False, # If set to true, indicates current stats is detected as and comparing with baseline stats.
        &quot;driftDetectionThreshold&quot;: 3.14, # This is the threshold used when detecting drifts, which is set in FeatureMonitor.FeatureSelectionConfig.FeatureConfig.drift_threshold
        &quot;featureId&quot;: &quot;A String&quot;, # Feature Id.
        &quot;featureMonitorId&quot;: &quot;A String&quot;, # The ID of the FeatureMonitor that this FeatureStatsAndAnomaly generated according to.
        &quot;featureMonitorJobId&quot;: &quot;A String&quot;, # The ID of the FeatureMonitorJob that generated this FeatureStatsAndAnomaly.
        &quot;featureStats&quot;: &quot;&quot;, # Feature stats. e.g. histogram buckets. In the format of tensorflow.metadata.v0.DatasetFeatureStatistics.
        &quot;statsTime&quot;: &quot;A String&quot;, # The timestamp we take snapshot for feature values to generate stats.
      },
    ],
    &quot;totalSlotMs&quot;: &quot;A String&quot;, # Output only. BigQuery slot milliseconds consumed.
  },
  &quot;labels&quot;: { # Optional. The labels with user-defined metadata to organize your FeatureMonitorJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureMonitor(System labels are excluded).&quot; System reserved label keys are prefixed with &quot;aiplatform.googleapis.com/&quot; and are immutable.
    &quot;a_key&quot;: &quot;A String&quot;,
  },
  &quot;name&quot;: &quot;A String&quot;, # Identifier. Name of the FeatureMonitorJob. Format: `projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_monitor}/featureMonitorJobs/{feature_monitor_job}`.
  &quot;triggerType&quot;: &quot;A String&quot;, # Output only. Trigger type of the Feature Monitor Job.
}</pre>
</div>

<div class="method">
    <code class="details" id="list">list(parent, filter=None, orderBy=None, pageSize=None, pageToken=None, x__xgafv=None)</code>
  <pre>List feature monitor jobs.

Args:
  parent: string, Required. The resource name of the FeatureMonitor to list FeatureMonitorJobs. Format: `projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_monitor}` (required)
  filter: string, Optional. Lists the FeatureMonitorJobs that match the filter expression. The following fields are supported: * `create_time`: Supports `=`, `!=`, `&lt;`, `&gt;`, `&lt;=`, and `&gt;=` comparisons. Values must be Examples: * `create_time &gt; &quot;2020-01-01&quot;` FeatureMonitorJobs created after 2020-01-01.
  orderBy: string, Optional. A comma-separated list of fields to order by, sorted in ascending order. Use &quot;desc&quot; after a field name for descending. Supported Fields: * `create_time`
  pageSize: integer, Optional. The maximum number of FeatureMonitorJobs to return. The service may return fewer than this value. If unspecified, at most 100 FeatureMonitorJobs will be returned. The maximum value is 100; any value greater than 100 will be coerced to 100.
  pageToken: string, Optional. A page token, received from a previous FeatureRegistryService.ListFeatureMonitorJobs call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeatureRegistryService.ListFeatureMonitorJobs must match the call that provided the page token.
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # Response message for FeatureRegistryService.ListFeatureMonitorJobs.
  &quot;featureMonitorJobs&quot;: [ # The FeatureMonitorJobs matching the request.
    { # Vertex AI Feature Monitor Job.
      &quot;createTime&quot;: &quot;A String&quot;, # Output only. Timestamp when this FeatureMonitorJob was created. Creation of a FeatureMonitorJob means that the job is pending / waiting for sufficient resources but may not have started running yet.
      &quot;description&quot;: &quot;A String&quot;, # Optional. Description of the FeatureMonitor.
      &quot;driftBaseFeatureMonitorJobId&quot;: &quot;A String&quot;, # Output only. FeatureMonitorJob ID comparing to which the drift is calculated.
      &quot;driftBaseSnapshotTime&quot;: &quot;A String&quot;, # Output only. Data snapshot time comparing to which the drift is calculated.
      &quot;featureSelectionConfig&quot;: { # Feature selection configuration for the FeatureMonitor. # Output only. Feature selection config used when creating FeatureMonitorJob.
        &quot;featureConfigs&quot;: [ # Optional. A list of features to be monitored and each feature&#x27;s drift threshold.
          { # Feature configuration.
            &quot;driftThreshold&quot;: 3.14, # Optional. Drift threshold. If calculated difference with baseline data larger than threshold, it will be considered as the feature has drift. If not present, the threshold will be default to 0.3. Must be in range [0, 1).
            &quot;featureId&quot;: &quot;A String&quot;, # Required. The ID of the feature resource. Final component of the Feature&#x27;s resource name.
          },
        ],
      },
      &quot;finalStatus&quot;: { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Final status of the FeatureMonitorJob.
        &quot;code&quot;: 42, # The status code, which should be an enum value of google.rpc.Code.
        &quot;details&quot;: [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
          {
            &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
          },
        ],
        &quot;message&quot;: &quot;A String&quot;, # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
      },
      &quot;jobSummary&quot;: { # Summary from the FeatureMonitorJob. # Output only. Summary from the FeatureMonitorJob.
        &quot;featureStatsAndAnomalies&quot;: [ # Output only. Features and their stats and anomalies
          { # Stats and Anomaly generated by FeatureMonitorJobs. Anomaly only includes Drift.
            &quot;distributionDeviation&quot;: 3.14, # Deviation from the current stats to baseline stats. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.
            &quot;driftDetected&quot;: True or False, # If set to true, indicates current stats is detected as and comparing with baseline stats.
            &quot;driftDetectionThreshold&quot;: 3.14, # This is the threshold used when detecting drifts, which is set in FeatureMonitor.FeatureSelectionConfig.FeatureConfig.drift_threshold
            &quot;featureId&quot;: &quot;A String&quot;, # Feature Id.
            &quot;featureMonitorId&quot;: &quot;A String&quot;, # The ID of the FeatureMonitor that this FeatureStatsAndAnomaly generated according to.
            &quot;featureMonitorJobId&quot;: &quot;A String&quot;, # The ID of the FeatureMonitorJob that generated this FeatureStatsAndAnomaly.
            &quot;featureStats&quot;: &quot;&quot;, # Feature stats. e.g. histogram buckets. In the format of tensorflow.metadata.v0.DatasetFeatureStatistics.
            &quot;statsTime&quot;: &quot;A String&quot;, # The timestamp we take snapshot for feature values to generate stats.
          },
        ],
        &quot;totalSlotMs&quot;: &quot;A String&quot;, # Output only. BigQuery slot milliseconds consumed.
      },
      &quot;labels&quot;: { # Optional. The labels with user-defined metadata to organize your FeatureMonitorJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureMonitor(System labels are excluded).&quot; System reserved label keys are prefixed with &quot;aiplatform.googleapis.com/&quot; and are immutable.
        &quot;a_key&quot;: &quot;A String&quot;,
      },
      &quot;name&quot;: &quot;A String&quot;, # Identifier. Name of the FeatureMonitorJob. Format: `projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_monitor}/featureMonitorJobs/{feature_monitor_job}`.
      &quot;triggerType&quot;: &quot;A String&quot;, # Output only. Trigger type of the Feature Monitor Job.
    },
  ],
  &quot;nextPageToken&quot;: &quot;A String&quot;, # A token, which can be sent as ListFeatureMonitorJobsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.
}</pre>
</div>

<div class="method">
    <code class="details" id="list_next">list_next()</code>
  <pre>Retrieves the next page of results.

        Args:
          previous_request: The request for the previous page. (required)
          previous_response: The response from the request for the previous page. (required)

        Returns:
          A request object that you can call &#x27;execute()&#x27; on to request the next
          page. Returns None if there are no more items in the collection.
        </pre>
</div>

</body></html>